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Product Validation
MarketingMind
BASES
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analytics.php)
(/#linkedin) BASES
LinkedIn
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Twitter
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Email
(Booz-AllenFacebook
Sales Estimating System)
is a
STM which integrates consumer response data
with manufacturers’ marketing plans to assess the
volumetric potential of concepts and products prior
to introduction.
Product
Validation


The system was developed in 1977 by Lynn Y.S.
Lin who at the time was with Burke Marketing
Research. Lin was inspired by work on marketing
simulators at Pillsbury where he was working prior
to joining Burke. BASES was acquired by
Nielsen in 1998.
Product
Validation
(~pv- BASES Premise
product-Consumers do not usually do what they claim to
do; and often the difference between claims and
validation.php)
behaviours is very significant. This inconvenient
truth, which complicates market research in
general, must not be overlooked in product
validation.
Moments
of Truth As with other STMs, BASES rides on the premise
there exists a strong correlation between
(~pv- that
consumers’ claimed purchase behaviour and what
subsequently transpires in the marketplace. While
momentsconsumers overstate their intended purchase
ofbehaviour, they tend to do so with consistency.
truth.php)
It has been observed that the level of
overstatement varies by country, by culture, and by
measure. With a database of about 200,000
concept tests (as of 2014), BASES is able to
accurately estimate the adjustment factors required
to deflate the respondents’ claims such that they
closely reflect their behaviour.
Launch
Validation
Methods
(~pv- Model Structure
validationmethods.php)
Marketing
Analytics
Workshop
In an analyticsdriven business
environment, this
analytics-centred
consumer
marketing
workshop is
tailored to the
needs of
consumer
analysts,
marketing
researchers,
brand managers,
category
managers and
seasoned
marketing and
retailing
professionals.
What they
SHOULD
TEACH at
Business
Schools
Simulated
Test
Markets
(~pvSTM.php)
BASES
(~pv- Exhibit 11.5 BASES overview.
An overview of the model is provided in Exhibit
BASES.php)
11.5. BASES essentially takes consumer response
data (what people say they will do), deflates it to
adjust for overstatement, and adjusts for the
impact of marketing activities to yield behavioural
data (a forecast of what people will actually do).
Controlled
Store
Data Collection
Test
(~pvCST.php)
Product
Launch
Evaluation
(~pvExhibit 11.6 Data collection at concept and product
product-stage.
launch- Online is the preferred and primary mode of data
collection as it yields considerable savings in time
evaluation.php)
and cost of study. BASES has e-Panels in a
ParfittCollins
Model
(~pv-
number of markets in North America, Europe and
Asia; the largest amongst these is the U.S. e-Panel,
comprising 125,000.
Where studies require face-to-face interaction (e.g.
sniff or taste tests), mall intercept, controlled
location tests and door to door methods are used
for interviewing respondents.
Is marketing
education fluffy
too?
Experiential
Learning
via
Simulators
| Best Way
to Train
Marketers
Marketing
simulators impart
much needed
combat
experiences,
equipping
practitioners with
the skills to
succeed in the
consumer market
battleground.
They combine
theory with
practice, linking
the classroom
with the
consumer
marketplace.
two stage interviewing process is depicted in
parfitt- The
Exhibit 11.6. The concept stage, where
respond to questions on the product
collins- respondents
concept, yields information on product trial.
model.php)
In case of face-to-face interviews, those
respondents who indicate they will not try the
product (“definitely would not try”, “probably would
not try”) are dropped from the product placement
stage. For e-Panel surveys however, all
respondents are moved to the product placement
stage, and receive samples. After allowing
respondents time to use the product samples, a
post-usage interview is conducted to obtain
information on respondents’ likelihood to
repurchase the product.
TRB
Model
(~pvTRBmodel.php)
Bass
Diffusion
Model
(~pvbassdiffusionExhibit 11.7 Example of a concept board (sourced
model.php)
from a student project, where ambrosia is a fictional
beverage category).
During the concept stage, either a concept board
(like the one shown in Exhibit 11.7) or a commercial
New Product
Development
is used for conveying the product concept and the
(~np-newbrand’s positioning. The board contains the
productdevelopment.php)information that will be communicated by
Product Design advertising as well as details on prices, sizes and
(~pd-product- varieties. Other than that, no additional information
design.php)
about the brand or competitor’s products is
Product Validation
(~pv-product- provided.
validation.php)
Analysis and Forecasting
Marketing
Education
How to Choose
the Right
Marketing
Simulator (~arHow-to-Choosethe-RightMarketingSimulator.php)
Self-Learners:
Experiential
Exhibit 11.8 Purchase intent — proportion of
Learning to Adapt
to the New Age ofrespondent across a 5-point rating scale.
Marketing (~arThe concept and after-use surveys obtain
self-learnersexperientialinformation for the purpose of volume forecasting.
learning-to-copewith-the-new- This includes purchase intent, purchase quantity
norms-of(i.e. the quantity respondents’ claim they will buy
marketing.php) should they try the product), and the frequency of
Negotiation Skills
purchasing should they continue to buy. The new
Training for
product is rated on the factors that typically evoke
Retailers,
Marketers, Trade consumers’ desire to purchase, for instance,
Marketers and
novelty, likeability, credibility and affordability.
Category
Managers (~ar- Information is also obtained on product usage, its
negotiationsskills-training.php)perception on key image and performance
attributes, suggested improvement, drivers and
Simulators
becoming
inhibiters, and the source of volume.
essential Training
Platforms (~ar- Purchase intent is measured on a 5-point rating
marketingscale similar to the one shown in the example in
educationsimulatorsExhibit 11.8. Considering that it pertains to
becomingessential-training-respondents’ claimed intent to purchase, we need
platforms.php) benchmarks to interpret this information. Whether
What they
the top 2 box scores of 41% and 81% for concept
SHOULD TEACH
and after-use purchase intent are good or bad
at Business
depends on how they compare with the BASES
Schools (~arwhat-theybenchmarks.
should-teach-atbusinessBASES database of about 200,000 tests is the
schools.php)
primary device used for interpretation. It serves as
Experiential
Learning through the source for benchmarks for all key measures,
Marketing
both at the concept and after-use phase. It is noted
Simulators (~arthat while after-use purchase intent strongly
experientiallearningcorrelates with in-market success, purchase intent
marketingsimulators.php) at the concept phase is not as good a reflection of
in-market success. Success targets accordingly
are derived from the after-use scores obtained for
products that were tested by BASES and that
subsequently achieved in-market success. Should
a new product score higher than the BASES
targets, it will have a high chance for success.
To generate a forecast BASES requires the
following inputs on the marketing plan for the new
product:
Introduction dates
Budget
Distribution and out-of-stock across retail
channels
Advertising schedule
Consumer promotion schedule
Trade promotion schedule
Retail sales for category and company’s
internal sales data
Seasonality
To the extent that execution is not in sync with
plan, actual sales volume would differ from the
BASES estimates. It is however possible to revise
volume estimates based on revisions to the
marketing plan.
Exhibit 11.9 Volume estimation.
The volume is forecasted by decomposing total
sales into trial and repeat volume, as depicted in
Exhibit 11.9. The forecast which pertains to the first
two years of launch, yields trial volume, repeat
volume, and consumption in terms of average
frequency of purchase and the average quantity
per occasion.
In terms of key deliverables, BASES provides an
estimate of a new product’s volume potential. It
also estimates the product’s source of growth —
how much the new product will cannibalize the
company’s brands, and how much it will gain from
competitors. In addition research diagnostics
reveal the strengths and weaknesses of the new
product initiative, and insights on how to improve
the product, its mix and the execution plan.
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